This question already has answers here:
Is floating point math broken?
(31 answers)
Closed 8 years ago.
i am facing this problem in python below is the code in python
>>> p=350.
>>> p-=0.1
>>> p-=0.1
>>> print p-349.8
-5.68434188608e-14
>>>
i have checked this program many times and i think the output of print p-349.8
should have come 0.
i have also tried this in other languages too in c++ , Java and python
and i want output to come 0.0
please help
Yes, all programming languages deal in base-2 numbers and therefore it is difficult to accurately express a floating point number as a base-10.
You could perhaps use the Decimal Class
Related
This question already has answers here:
Is floating point math broken?
(31 answers)
Closed 1 year ago.
I use math.pi with python:
import Decimal as dc
dc.getcontext().prec=100
pi = dc.Decimal(math.pi)
and I get:
3.141592653589793115997963468544185161590576171875
and on Internet, I get:
3,141592653589793238462643383279502884197169399375
Why doesn't python give a good value? How to improve the situation?
I tried with and without Decimal.
As indicated in the comments and in the documentation of Python math module, math.pi holds a floating-point value. Floating-point is inaccurate by design, because there is a finite number of bits dedicated to keeping the precision. You can read https://docs.python.org/3/tutorial/floatingpoint.html to understand how float is represented, and how this will impact you during programming (in all languages, not only Python).
How to get your accurate value of pi? As mentioned by Tom Karzes, you can use Decimal module and feed it with as many digits as you want. Let's take the first 30 digits of pi from https://www.angio.net/pi/digits/pi1000000.txt, and your code would look like this:
pi_30_decimal_places = Decimal("3.141592653589793238462643383279")
This question already has answers here:
Is floating point math broken?
(31 answers)
Closed 2 years ago.
I came across the following strange result in Python (I use Spyder environment). Any idea what is going on? And how can I fix this? I truly don't want to put 20 zeros in front of my variable nor using numpy for such a simple work makes sense!
int(121212000000000000000000000000000000000000000000000000)
Out[27]: 121212000000000000000000000000000000000000000000000000
int(121212*1e20)
Out[28]: 12121199999999999802867712
int(121212*10e20)
Out[29]: 121211999999999993733709824
It has to do with floating point precision.
You can use the decimal module like so:
>>> from decimal import Decimal
>>> Decimal(121212) * Decimal('10e20')
Decimal('121212000000000000000000000')
For more info, see the following Python tutorial.
This question already has answers here:
Is floating point math broken?
(31 answers)
Closed 3 years ago.
I was using a simple for loop to add numbers but I found a strange result when adding float.
Can you explain why I have the following output ?
1.1
1.2000000000000002
1.3000000000000003
1.4000000000000004
1.5000000000000004
1.6000000000000005
1.7000000000000006
1.8000000000000007
1.9000000000000008
2.000000000000001
2.100000000000001
2.200000000000001
2.300000000000001
2.4000000000000012
2.5000000000000013
2.6000000000000014
2.7000000000000015
2.8000000000000016
2.9000000000000017
3.0000000000000018
3.100000000000002
3.200000000000002
3.300000000000002
3.400000000000002
3.500000000000002
3.6000000000000023
3.7000000000000024
3.8000000000000025
3.9000000000000026
This is based on Anaconda Spyder
a = 1
for i in range(1,30):
a = a+0.1
print(a)
It's a known limitation of floating point arithmetic, computers cannot store infinitely precise floating point numbers. See python docs.
This question already has answers here:
Why does floating-point arithmetic not give exact results when adding decimal fractions?
(31 answers)
Closed 5 years ago.
I've run a simple python command and it derives the following result. Can anyone tell me why?
a=[[0.12,0.35],[0.66,0.79]]
b=[[10*i,10*j] for i,j in a]
and I got the following result:
b=[[1.2, 3.5], [6.6000000000000005, 7.9]]
This is simple representation "error". Binary numbers do not represent decimal values with prefect accuracy, any more than a terminating decimal can accurately represent, say, 1/7.
0.66 is a decimal whose binary representation is just a hair high (actually, they're all going to be a little "off", but this is the only one that shows at a factor of only 10). You can "fix" this by switching to a decimal data type.
This question already has answers here:
Is floating point arbitrary precision available?
(5 answers)
Closed 7 years ago.
I am using python and have something like this-
a=3.472556691305291e-97
b=2.0842803001689662e-120
c=a/(a+b)
print(c)
I am getting value=1.0 . But I want the exact answer.Is there some way I can improve my accuracy here?
You can use an external library, such as mpmath, to get arbitrary precision floating point numbers.
Use the mpf type for the numbers, as shown in the examples in the documentation:
>>> mpf(4)
mpf('4.0')
>>> mpf(2.5)
mpf('2.5')
>>> mpf("1.25e6")
mpf('1250000.0')
>>> mpf(mpf(2))
mpf('2.0')
>>> mpf("inf")
mpf('+inf')